Learning to Forget -- Hierarchical Episodic Memory for Lifelong Robot Deployment

H²-EMV addresses a critical bottleneck in robotics: the 'infinite data' problem of lifelong video and sensor streams. While the hierarchical memory approach is technically sound, the project currently exists as a fresh research implementation (0 stars, 4 forks) with no community momentum. Its defensibility is low because the core problem—intelligent memory pruning—is a primary focus for major frontier labs (OpenAI/Figure, Tesla, and Google DeepMind). As humanoid robots move from labs to homes, memory management will be baked into the underlying 'Robot OS' at the platform level. The specific 'learning to forget' via user interaction is a novel niche, but likely to be absorbed as a standard feature of multimodal LLMs or specialized robotic controllers. Without a massive proprietary dataset or a highly optimized hardware-specific implementation, this remains a valuable reference algorithm rather than a defensible product.